Sankey Diagram can be built in
R using the networkD3 package. This posts
displays basic example, focusing on the different input formats that
can be used.
A Sankey diagram represents flows, i.e. weigthed connections going from one node to another. Input data can be stored in 2 different formats:
This post describes how to build a basic Sankey diagram from these 2 types of input.
A connection data frame lists all the connections one by one in a data frame.
Usually you have a source and a
target column. You can add a third column that gives
further information for each connection, like the value of the flow.
This is the format you need to use the
networkD3 library. Let’s build a connection data frame
and represent it as a Sankey diagram:
# Library
library(networkD3)
library(dplyr)
# A connection data frame is a list of flows with intensity for each flow
links <- data.frame(
source=c("group_A","group_A", "group_B", "group_C", "group_C", "group_E"),
target=c("group_C","group_D", "group_E", "group_F", "group_G", "group_H"),
value=c(2,3, 2, 3, 1, 3)
)
# From these flows we need to create a node data frame: it lists every entities involved in the flow
nodes <- data.frame(
name=c(as.character(links$source),
as.character(links$target)) %>% unique()
)
# With networkD3, connection must be provided using id, not using real name like in the links dataframe.. So we need to reformat it.
links$IDsource <- match(links$source, nodes$name)-1
links$IDtarget <- match(links$target, nodes$name)-1
# Make the Network
p <- sankeyNetwork(Links = links, Nodes = nodes,
Source = "IDsource", Target = "IDtarget",
Value = "value", NodeID = "name",
sinksRight=FALSE)
p
# save the widget
# library(htmlwidgets)
# saveWidget(p, file=paste0( getwd(), "/HtmlWidget/sankeyBasic1.html"))An incidence matrix is square or rectangle.
Row and column names are node names. The item in row x and column y represents the flow between x and y. In the Sankey diagram we represent all flows that are over 0.
Since the networkD3 library expects a connection data
frame, we will fist convert the dataset, and then re-use the code
from above.
# Library
library(networkD3)
library(dplyr)
# Create an incidence matrix. Usually the flow goes from the row names to the column names.
# Remember that our connection are directed since we are working with a flow.
set.seed(1)
data <- matrix(sample( seq(0,40), 49, replace=T ), 7, 7)
data[data < 35] <- 0
colnames(data) = rownames(data) = c("group_A", "group_B", "group_C", "group_D", "group_E", "group_F", "group_G")
# Transform it to connection data frame with tidyr from the tidyverse:
links <- data %>%
as.data.frame() %>%
rownames_to_column(var="source") %>%
gather(key="target", value="value", -1) %>%
filter(value != 0)
# From these flows we need to create a node data frame: it lists every entities involved in the flow
nodes <- data.frame(
name=c(as.character(links$source), as.character(links$target)) %>%
unique()
)
# With networkD3, connection must be provided using id, not using real name like in the links dataframe.. So we need to reformat it.
links$IDsource <- match(links$source, nodes$name)-1
links$IDtarget <- match(links$target, nodes$name)-1
# Make the Network
p <- sankeyNetwork(Links = links, Nodes = nodes,
Source = "IDsource", Target = "IDtarget",
Value = "value", NodeID = "name",
sinksRight=FALSE)
p
# save the widget
# library(htmlwidgets)
# saveWidget(p, file=paste0( getwd(), "/HtmlWidget/sankeyBasic2.html"))Related chart types
